Alternatives to Capistrano logo

Alternatives to Capistrano

Fabric, Shipit, Docker, Ansible, and Chef are the most popular alternatives and competitors to Capistrano.
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What is Capistrano and what are its top alternatives?

Capistrano is a popular open-source tool used for automating deployment tasks in Ruby on Rails applications. It allows developers to define deployment tasks, manage multiple servers, and roll back deployments if needed. However, Capistrano has limitations such as a steeper learning curve, especially for beginners, and limited support for non-Ruby projects.

  1. Fabric: Fabric is a Python-based deployment tool that simplifies remote execution and deployment tasks. Key features include task automation, parallel execution, and availability of a large community for support. Pros include its simplicity and flexibility, while cons include limited Windows support.
  2. Ansible: Ansible is an automation tool that can be used for deployment, configuration management, and orchestration. Its key features include easy setup, agentless architecture, and idempotent tasks. Pros include simplicity and broad platform support, while cons include slower execution speed compared to Capistrano.
  3. Docker: Docker is a containerization platform that can be used for deploying applications in isolated environments. Key features include lightweight containers, easy scalability, and portability. Pros include efficient resource utilization and improved consistency, while cons include the need for a strong understanding of containers.
  4. Chef: Chef is a configuration management tool that can also be used for deployment automation. It offers features such as infrastructure as code, continuous deployment, and dependency management. Pros include scalability and flexibility, while cons include a steeper learning curve compared to Capistrano.
  5. Fabric8: Fabric8 is an open-source integration platform that includes tooling for Kubernetes, Jenkins, and other DevOps-related tasks. Key features include pipeline automation, container orchestration, and continuous integration. Pros include comprehensive tooling and seamless integration, while cons include a more complex setup process.
  6. Rundeck: Rundeck is a job scheduling and automation tool that can be used for deploying applications and managing infrastructure tasks. Its features include role-based access control, job workflows, and integration with various tools. Pros include its user-friendly interface and scalability, while cons include a heavier resource footprint.
  7. Jenkins: Jenkins is a popular automation server that can be used for continuous integration and deployment tasks. Key features include extensibility through plugins, pipeline automation, and scalability. Pros include a large community and wide plugin support, while cons include a more complex setup compared to Capistrano.
  8. GitLab CI: GitLab CI is a continuous integration tool that offers deployment features as well. It provides features such as pipeline automation, version control integration, and Kubernetes support. Pros include seamless integration with GitLab repositories and robust CI/CD capabilities, while cons include a learning curve for beginners.
  9. Octopus Deploy: Octopus Deploy is a deployment automation tool that simplifies the deployment process for .NET applications. Key features include release management, deployment auditing, and multiple environment support. Pros include ease of use and scalability, while cons include limited support for non-.NET applications.
  10. SaltStack: SaltStack is a configuration management tool that can also be used for deployment automation. Its key features include remote execution, event-driven automation, and infrastructure orchestration. Pros include speed and scalability, while cons include a more complex setup process compared to Capistrano.

Top Alternatives to Capistrano

  • Fabric
    Fabric

    Fabric is a Python (2.5-2.7) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. It provides a basic suite of operations for executing local or remote shell commands (normally or via sudo) and uploading/downloading files, as well as auxiliary functionality such as prompting the running user for input, or aborting execution. ...

  • Shipit
    Shipit

    Shipit is an automation engine and a deployment tool written for node / iojs. Shipit was built to be a Capistrano alternative for people who don't know ruby, or who experienced some issues with it. If you want to write tasks in JavaScript and enjoy the node ecosystem, Shipit is also for you. ...

  • Docker
    Docker

    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere ...

  • Ansible
    Ansible

    Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use. ...

  • Chef
    Chef

    Chef enables you to manage and scale cloud infrastructure with no downtime or interruptions. Freely move applications and configurations from one cloud to another. Chef is integrated with all major cloud providers including Amazon EC2, VMWare, IBM Smartcloud, Rackspace, OpenStack, Windows Azure, HP Cloud, Google Compute Engine, Joyent Cloud and others. ...

  • Jenkins
    Jenkins

    In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project. ...

  • Mina
    Mina

    Mina works really fast because it's a deploy Bash script generator. It generates an entire procedure as a Bash script and runs it remotely in the server. Compare this to the likes of Vlad or Capistrano, where each command is run separately on their own SSH sessions. Mina only creates one SSH session per deploy, minimizing the SSH connection overhead. ...

  • Deployer
    Deployer

    A deployment tool written in PHP with support for popular frameworks out of the box ...

Capistrano alternatives & related posts

Fabric logo

Fabric

451
307
75
Simple, Pythonic remote execution and deployment
451
307
+ 1
75
PROS OF FABRIC
  • 23
    Python
  • 21
    Simple
  • 5
    Low learning curve, from bash script to Python power
  • 5
    Installation feedback for Twitter App Cards
  • 3
    Easy on maintainance
  • 3
    Single config file
  • 3
    Installation? pip install fabric... Boom
  • 3
    Easy to add any type of job
  • 3
    Agentless
  • 2
    Easily automate any set system automation
  • 1
    Flexible
  • 1
    Crash Analytics
  • 1
    Backward compatibility
  • 1
    Remote sudo execution
CONS OF FABRIC
    Be the first to leave a con

    related Fabric posts

    Shipit logo

    Shipit

    36
    41
    6
    Pure JavaScript deployment tool used by Ghost blogging platform
    36
    41
    + 1
    6
    PROS OF SHIPIT
    • 2
      Simple
    • 2
      Great configuration
    • 2
      Agentless
    CONS OF SHIPIT
      Be the first to leave a con

      related Shipit posts

      Kir Shatrov
      Engineering Lead at Shopify · | 13 upvotes · 159.6K views

      Shipit, our deployment tool, is at the heart of Continuous Delivery at Shopify. Shipit is an orchestrator that runs and tracks progress of any deploy script that you provide for a project. It supports deploying to Rubygems, Pip, Heroku and Capistrano out of the box. For us, it's mostly kubernetes-deploy or Capistrano for legacy projects.

      We use a slightly tweaked GitHub flow, with feature development going in branches and the master branch being the source of truth for the state of things in production. When your PR is ready, you add it to the Merge Queue in ShipIt. The idea behind the Merge Queue is to control the rate of code that is being merged to master branch. In the busy hours, we have many developers who want to merge the PRs, but at the same time we don't want to introduce too many changes to the system at the same time. Merge Queue limits deploys to 5-10 commits at a time, which makes it easier to identify issues and roll back in case we notice any unexpected behaviour after the deploy.

      We use a browser extension to make Merge Queue play nicely with the Merge button on GitHub:

      Both Shipit and kubernetes-deploy are open source, and we've heard quite a few success stories from companies who have adopted our flow.

      #BuildTestDeploy #ContainerTools #ApplicationHosting #PlatformAsAService

      See more
      Docker logo

      Docker

      174.3K
      140.1K
      3.9K
      Enterprise Container Platform for High-Velocity Innovation.
      174.3K
      140.1K
      + 1
      3.9K
      PROS OF DOCKER
      • 823
        Rapid integration and build up
      • 692
        Isolation
      • 521
        Open source
      • 505
        Testa­bil­i­ty and re­pro­ducibil­i­ty
      • 460
        Lightweight
      • 218
        Standardization
      • 185
        Scalable
      • 106
        Upgrading / down­grad­ing / ap­pli­ca­tion versions
      • 88
        Security
      • 85
        Private paas environments
      • 34
        Portability
      • 26
        Limit resource usage
      • 17
        Game changer
      • 16
        I love the way docker has changed virtualization
      • 14
        Fast
      • 12
        Concurrency
      • 8
        Docker's Compose tools
      • 6
        Fast and Portable
      • 6
        Easy setup
      • 5
        Because its fun
      • 4
        Makes shipping to production very simple
      • 3
        It's dope
      • 3
        Highly useful
      • 2
        Does a nice job hogging memory
      • 2
        Open source and highly configurable
      • 2
        Simplicity, isolation, resource effective
      • 2
        MacOS support FAKE
      • 2
        Its cool
      • 2
        Docker hub for the FTW
      • 2
        HIgh Throughput
      • 2
        Very easy to setup integrate and build
      • 2
        Package the environment with the application
      • 2
        Super
      • 0
        Asdfd
      CONS OF DOCKER
      • 8
        New versions == broken features
      • 6
        Unreliable networking
      • 6
        Documentation not always in sync
      • 4
        Moves quickly
      • 3
        Not Secure

      related Docker posts

      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.2M views

      Our whole DevOps stack consists of the following tools:

      • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
      • Respectively Git as revision control system
      • SourceTree as Git GUI
      • Visual Studio Code as IDE
      • CircleCI for continuous integration (automatize development process)
      • Prettier / TSLint / ESLint as code linter
      • SonarQube as quality gate
      • Docker as container management (incl. Docker Compose for multi-container application management)
      • VirtualBox for operating system simulation tests
      • Kubernetes as cluster management for docker containers
      • Heroku for deploying in test environments
      • nginx as web server (preferably used as facade server in production environment)
      • SSLMate (using OpenSSL) for certificate management
      • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
      • PostgreSQL as preferred database system
      • Redis as preferred in-memory database/store (great for caching)

      The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

      • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
      • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
      • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
      • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
      • Scalability: All-in-one framework for distributed systems.
      • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
      See more
      Tymoteusz Paul
      Devops guy at X20X Development LTD · | 23 upvotes · 9.7M views

      Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

      It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

      I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

      We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

      If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

      The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

      Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

      See more
      Ansible logo

      Ansible

      19.1K
      15.4K
      1.3K
      Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine
      19.1K
      15.4K
      + 1
      1.3K
      PROS OF ANSIBLE
      • 284
        Agentless
      • 210
        Great configuration
      • 199
        Simple
      • 176
        Powerful
      • 155
        Easy to learn
      • 69
        Flexible
      • 55
        Doesn't get in the way of getting s--- done
      • 35
        Makes sense
      • 30
        Super efficient and flexible
      • 27
        Powerful
      • 11
        Dynamic Inventory
      • 9
        Backed by Red Hat
      • 7
        Works with AWS
      • 6
        Cloud Oriented
      • 6
        Easy to maintain
      • 4
        Vagrant provisioner
      • 4
        Simple and powerful
      • 4
        Multi language
      • 4
        Simple
      • 4
        Because SSH
      • 4
        Procedural or declarative, or both
      • 4
        Easy
      • 3
        Consistency
      • 2
        Well-documented
      • 2
        Masterless
      • 2
        Debugging is simple
      • 2
        Merge hash to get final configuration similar to hiera
      • 2
        Fast as hell
      • 1
        Manage any OS
      • 1
        Work on windows, but difficult to manage
      • 1
        Certified Content
      CONS OF ANSIBLE
      • 8
        Dangerous
      • 5
        Hard to install
      • 3
        Doesn't Run on Windows
      • 3
        Bloated
      • 3
        Backward compatibility
      • 2
        No immutable infrastructure

      related Ansible posts

      Tymoteusz Paul
      Devops guy at X20X Development LTD · | 23 upvotes · 9.7M views

      Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

      It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

      I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

      We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

      If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

      The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

      Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

      See more
      Sebastian Gębski

      Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

      See more
      Chef logo

      Chef

      1.3K
      1.1K
      345
      Build, destroy and rebuild servers on any public or private cloud
      1.3K
      1.1K
      + 1
      345
      PROS OF CHEF
      • 110
        Dynamic and idempotent server configuration
      • 76
        Reusable components
      • 47
        Integration testing with Vagrant
      • 43
        Repeatable
      • 30
        Mock testing with Chefspec
      • 14
        Ruby
      • 8
        Can package cookbooks to guarantee repeatability
      • 7
        Works with AWS
      • 3
        Has marketplace where you get readymade cookbooks
      • 3
        Matured product with good community support
      • 2
        Less declarative more procedural
      • 2
        Open source configuration mgmt made easy(ish)
      CONS OF CHEF
        Be the first to leave a con

        related Chef posts

        In late 2013, the Operations Engineering team at PagerDuty was made up of 4 engineers, and was comprised of generalists, each of whom had one or two areas of depth. Although the Operations Team ran its own on-call, each engineering team at PagerDuty also participated on the pager.

        The Operations Engineering Team owned 150+ servers spanning multiple cloud providers, and used Chef to automate their infrastructure across the various cloud providers with a mix of completely custom cookbooks and customized community cookbooks.

        Custom cookbooks were managed by Berkshelf, andach custom cookbook contained its own tests based on ChefSpec 3, coupled with Rspec.

        Jenkins was used to GitHub for new changes and to handle unit testing of those features.

        See more
        Marcel Kornegoor

        Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.

        For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.

        For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.

        Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.

        See more
        Jenkins logo

        Jenkins

        58.4K
        49.8K
        2.2K
        An extendable open source continuous integration server
        58.4K
        49.8K
        + 1
        2.2K
        PROS OF JENKINS
        • 523
          Hosted internally
        • 469
          Free open source
        • 318
          Great to build, deploy or launch anything async
        • 243
          Tons of integrations
        • 211
          Rich set of plugins with good documentation
        • 111
          Has support for build pipelines
        • 68
          Easy setup
        • 66
          It is open-source
        • 53
          Workflow plugin
        • 13
          Configuration as code
        • 12
          Very powerful tool
        • 11
          Many Plugins
        • 10
          Continuous Integration
        • 10
          Great flexibility
        • 9
          Git and Maven integration is better
        • 8
          100% free and open source
        • 7
          Github integration
        • 7
          Slack Integration (plugin)
        • 6
          Easy customisation
        • 6
          Self-hosted GitLab Integration (plugin)
        • 5
          Docker support
        • 5
          Pipeline API
        • 4
          Fast builds
        • 4
          Platform idnependency
        • 4
          Hosted Externally
        • 4
          Excellent docker integration
        • 3
          It`w worked
        • 3
          Customizable
        • 3
          Can be run as a Docker container
        • 3
          It's Everywhere
        • 3
          JOBDSL
        • 3
          AWS Integration
        • 2
          Easily extendable with seamless integration
        • 2
          PHP Support
        • 2
          Build PR Branch Only
        • 2
          NodeJS Support
        • 2
          Ruby/Rails Support
        • 2
          Universal controller
        • 2
          Loose Coupling
        CONS OF JENKINS
        • 13
          Workarounds needed for basic requirements
        • 10
          Groovy with cumbersome syntax
        • 8
          Plugins compatibility issues
        • 7
          Lack of support
        • 7
          Limited abilities with declarative pipelines
        • 5
          No YAML syntax
        • 4
          Too tied to plugins versions

        related Jenkins posts

        Tymoteusz Paul
        Devops guy at X20X Development LTD · | 23 upvotes · 9.7M views

        Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

        It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

        I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

        We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

        If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

        The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

        Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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        Thierry Schellenbach

        Releasing new versions of our services is done by Travis CI. Travis first runs our test suite. Once it passes, it publishes a new release binary to GitHub.

        Common tasks such as installing dependencies for the Go project, or building a binary are automated using plain old Makefiles. (We know, crazy old school, right?) Our binaries are compressed using UPX.

        Travis has come a long way over the past years. I used to prefer Jenkins in some cases since it was easier to debug broken builds. With the addition of the aptly named “debug build” button, Travis is now the clear winner. It’s easy to use and free for open source, with no need to maintain anything.

        #ContinuousIntegration #CodeCollaborationVersionControl

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            As of more basic stuff, we use HTML5, JavaScript (but with Vue.js too) and Webpack to handle the generation of all this.

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